[jira] [Updated] (SPARK-34682) Regression in "operating on canonicalized plan" check in CustomShuffleReaderExec

["Dongjoon Hyun (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-34682?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Dongjoon Hyun updated SPARK-34682:
----------------------------------
        Parent: SPARK-33828
    Issue Type: Sub-task  (was: Bug)

> Regression in "operating on canonicalized plan" check in CustomShuffleReaderExec
> --------------------------------------------------------------------------------
>
>                 Key: SPARK-34682
>                 URL: https://issues.apache.org/jira/browse/SPARK-34682
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SQL
>    Affects Versions: 3.1.1
>            Reporter: Andy Grove
>            Priority: Minor
>             Fix For: 3.2.0, 3.1.2
>
>
> In Spark 3.0.2 if I attempt to execute on a canonicalized version of CustomShuffleReaderExec I get an error "operating on canonicalized plan", as expected.
> There is a regression in Spark 3.1.1 where this check can never be reached because of a new call to sendDriverMetrics that was added prior to the check. This method will fail if operating on a canonicalized plan because it assumes the existence of metrics that do not exist if this is a canonicalized plan.
> {code:java}
>  private lazy val shuffleRDD: RDD[_] = {
>   sendDriverMetrics()
>   shuffleStage.map { stage =>
>     stage.shuffle.getShuffleRDD(partitionSpecs.toArray)
>   }.getOrElse {
>     throw new IllegalStateException("operating on canonicalized plan")
>   }
> }{code}
> The specific error looks like this:
> {code:java}
> java.util.NoSuchElementException: key not found: numPartitions
>         at scala.collection.immutable.Map$EmptyMap$.apply(Map.scala:101)
>         at scala.collection.immutable.Map$EmptyMap$.apply(Map.scala:99)
>         at org.apache.spark.sql.execution.adaptive.CustomShuffleReaderExec.sendDriverMetrics(CustomShuffleReaderExec.scala:122)
>         at org.apache.spark.sql.execution.adaptive.CustomShuffleReaderExec.shuffleRDD$lzycompute(CustomShuffleReaderExec.scala:182)
>         at org.apache.spark.sql.execution.adaptive.CustomShuffleReaderExec.shuffleRDD(CustomShuffleReaderExec.scala:181)
>         at org.apache.spark.sql.execution.adaptive.CustomShuffleReaderExec.doExecuteColumnar(CustomShuffleReaderExec.scala:196)
>  {code}
> I think the fix is simply to avoid calling sendDriverMetrics if the plan is canonicalized and I am planning on creating a PR to fix this.



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